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When Do Judges Throw the Book at Companies? The Influence of Partisanship in Corporate Prosecutions

Review of Financial Studies 2026
We document that judges’ political affiliations are strongly associated with the level of judicial penalties levied against companies. For example, Republican-appointed judges impose larger fines for hiring illegal immigrants, while Democrat-appointed judges impose larger fines for pollution- and environment-related violations. Time-series variation suggests that political partisanship, not fixed ideological differences, drives these findings. The differences become amplified when higher-court judicial vacancies exist and in the months before national elections. Our findings highlight the importance of political polarization for U.S. companies and illustrate how judicial composition can affect firms’ incentive to avoid violating laws connected to partisan issues.

Macroeconomic Expectations and Credit Card Spending

Review of Financial Studies 2026
We examine how macroeconomic expectations affect consumer decisions, using an experiment with 2,872 credit card customers at a large commercial bank. In the experiment, participants are randomized into receiving expert forecasts of inflation and the nominal exchange rate. We find that forecasts shift inflation and exchange rate expectations, but do not change spending or self-reported consumption plans as predicted by standard models of intertemporal choice. Results from a supplementary survey experiment suggest that consumers are sophisticated enough to anticipate nominal rigidities and reduce spending on durables for precautionary reasons, counteracting the effects predicted by standard models of intertemporal optimization.

Payment for Order Flow and Option Internalization

Review of Financial Studies 2026 open access
Option wholesalers specialize in purchasing and executing against retail option order flow. Orders are internalized via auctions (which provide price improvement) and the limit order book. Designated market makers (DMMs) have a key advantage in internalizing limit order book trades: they obtain the first five contracts of any order they bring to an exchange where they are a DMM. We exploit variation in DMM assignments and allocation rules to highlight how these rules create a barrier to entry in option wholesaling that does not exist for equity wholesaling, protecting wholesaler profits and high option PFOF.

Cooling Auction Fever: Evidence from the Housing Market

Review of Financial Studies 2026
We study the effects of underquoting, the practice of setting listing prices below sellers’ reservation values, on housing auctions. Laws introduced in Australia to deter underquoting lead to higher listing prices, but also to declines in sales prices and sales probabilities. We develop a quantitative model to formalize predictions under different assumptions about bidders’ information and rationality. The effects of the laws are matched by a version of the model in which participating bidders overbid. While both behavioral biases arising during the auction and switching costs can explain overbidding, empirical and survey evidence points to behavioral biases as the main mechanism.

Financial Intermediaries and the Yield Curve

Review of Financial Studies 2026
I study the yield curve dynamics in a general equilibrium model with financial intermediaries facing financing constraints. When constraints bind, intermediaries reallocate their portfolios, causing deadweight losses in aggregate consumption, thus affecting savers’ marginal utility. Because the yield curve is a forecast of marginal utility, intermediaries’ constraints show up, via general equilibrium forces, in long-term yields. I show that the mechanism connecting intermediaries’ constraints and long-term yields produces highly nonlinear interest rate dynamics and a positive real term premium in equilibrium. I extend the analysis to the nominal yield curve using a simple Taylor rule.

Algorithmic Pricing and Liquidity in Securities Markets

Review of Financial Studies 2026 open access
We study “Algorithmic Market Makers” (AMs) that use Q-learning algorithms to set prices for a risky asset. We find that while AMs successfully adapt to adverse selection, they struggle to learn competitive pricing strategies. This failure is driven by limited experimentation and noisy feedback regarding the profitability of undercutting a competitor. Consequently, an increase in AMs’ profit volatility tends to result in less competitive market outcomes. These features leave identifiable patterns: for example, AMs earn higher rents in the absence of adverse selection, and their bid-ask spreads respond asymmetrically to symmetric shocks to their costs.

The Present Value of Future Market Power

Review of Financial Studies 2026
We introduce a present-value identity relating a firm’s market value to expected future markups, output growth, discount rates, and investments. Distinguishing current from expected markups reveals five empirical facts: (1) Expected markups account for half the rise in U.S. firm values since 1980. (2) The rise in aggregate expected markups reflects market-share reallocation toward high-expected-markup firms and within-firm increases. (3) Expected markups are linked to intangible investments. (4) They relate negatively to discount rates over time but (5) positively to abnormal returns across firms. Finally, variation in long-term expected markups is primarily associated with asset prices rather than current markups.

Is Fraud Contagious? Social Connections and the Looting of COVID Relief Programs

Review of Financial Studies 2026 open access
Fraud indicators within the Paycheck Protection Program (PPP), a major COVID relief program, are highly geographically concentrated. ZIP codes and counties with high rates of suspicious PPP loans are strongly socially connected, with evidence that fraud spreads spatially over time through social networks. Individuals in suspicious social media groups have higher rates of PPP fraud, and socially connected ZIP codes frequently use the same specific FinTech lenders, consistent with social networks influencing detailed loan decisions. Our findings suggest that more proactive data analysis is needed for fraud prevention, detection, and prosecution to prevent the social spread of fraudulent schemes.

The Impact of Carcinogenic Risk Exposure on Housing Values: Estimates from Chemical Reclassifications

Review of Financial Studies 2026 open access
We quantify the impact of perceived cancer risk on housing values using widely advertised national reclassifications of chemical carcinogenicity in the United States. Combining these information events with an empirical design that compares changes in house values closer to affected toxic plants against those farther away isolates the effect of cancer risk news from other local factors. Focusing on plants previously emitting reclassified carcinogenic chemicals, we estimate a 1–2% decline in housing values within a 3-mile radius compared to those located farther away. The effects are stronger in areas with higher media presence underscoring the role of salience as a mechanism.